To address the challenges of insufficient wide-area information perception, poor robustness in multi-target tracking, and low accuracy in dangerous behavior recognition during major public security tasks, this paper integrates key technologies such as wide-area high-definition multi-source image stitching, deep learning-based image recognition, automatic multi-target tracking and early warning, and posture-behavior recognition of dangerous targets. A multi-modal panoramic imaging collaborative optimization framework is proposed, and a highly integrated wide-area surveillance system is developed. First, a requirement model for wide-area surveillance tasks is established using the AHP（Analytic Hierarchy Process）, based on which the overall system architecture, hardware architecture, and software algorithm architecture are optimized. Second, 360° wide-area surveillance is achieved through heterogeneous sensor collaborative perception and panoramic stitching, while deep learning networks realize multi-type target recognition with a success rate exceeding 90% in self-tested environments. Third, a multi-feature target tracking algorithm incorporating spatial attention feature extraction networks and subspace reconstruction mechanisms is designed, achieving a multi-target tracking success rate of 93.98% in self-tested environments. Further, a temporal-spatial dual-stream action recognition model（TSAR）is constructed, yielding dangerous behavior recognition accuracy exceeding 90% in self-tested environments. Experimental results demonstrate that this system effectively supports wide-area surveillance, target tracking/locking, and intelligent early warning in public activity scenarios, providing reliable solutions for complex dynamic security tasks.

With the advancement of transmission line inspection technology, infrared imaging has become increasingly crucial for detecting line faults and potential hazards. However, traditional image segmentation methods often struggle with accuracy when dealing with complex backgrounds and multispectral information. A two-dimensional maximum entropy threshold image segmentation algorithm based on multispectral fusion to enhance the segmentation performance of infrared images of transmission lines is proposed in the paper. The method involves fusing multispectral information obtained from infrared imaging sensors, and then applies the maximum entropy threshold algorithm to the fused image to accurately extract key features within the transmission lines. Experimental results show that the proposed algorithm achieves an image correlation coefficient of 0.907 8 and a structural similarity of 0.913 2. Compared with the traditional one-dimensional maximum entropy threshold algorithm, the correlation coefficient and structural similarity have improved by approximately 6.6% and 21.4%, respectively. Moreover, the relative error in image segmentation using the proposed method is reduced by more than 10% compared to the one-dimensional algorithm. This approach offers more reliable technical support for the intelligent inspection of transmission lines and holds significant practical application value.

In the domain of surveillance and detection, acquiring distance information about targets is crucial. Traditional ranging methods, such as radar and laser ranging, have limitations due to their active emission of electromagnetic or laser signals towards the target during operation, which can potentially reveal their own position. To address this issue, an intelligent ranging algorithm based on monocular dual-modal image processing is proposed. This algorithm employs computer vision techniques and deep learning models to achieve non-contact passive ranging by capturing and analyzing images of the target. The process begins with obtaining a sequence of images of the target using a monocular camera, followed by feature extraction of these images through pre-trained deep neural network（DNN）models. It then combines principles of image formation with deep learning technology to estimate the relative distance between the target and the observation point by predicting ranging errors via neural networks. Under specific constraints, the ranging error of this algorithm is less than 10%. Ablation studies on continuous frames and long-term sequence correction strategies show that compared with single-frame input, the average error is reduced by 0.74 km, and the average percentage error is reduced by 3.69%, making it significant for applications in long-distance passive ranging. This approach represents a promising advancement in passive ranging technology, offering enhanced accuracy and reliability without compromising the concealment of the observation platform.

Special optical fibers such as elliptical core polarization maintaining fibers, radiation resistant fibers, and erbium-doped fibers are more susceptible to harsh environments such as high and low temperatures in practical applications due to their unique application scenarios. Strict environmental testing is required before application, and optical fibers with mismatched coating geometries are prone to separation defects in practical applications or after environmental testing. This article theoretically analyzes the functional relationship between the maximum shear force required for fiber coating separation and the shear strength of the coating, and determines that the main causes of coating delamination defects are the mismatch in the ratio between the inner and outer coatings of the fiber and the large range of environmental temperature changes. This article verifies the influence of different thickness ratios of inner and outer coatings on the shear strength and delamination defects of optical fibers through coating peeling tests and temperature cycling tests, which is consistent with the theoretical analysis results. The research results of this article have certain guiding significance for optimizing the geometric structure of optical fiber coatings and improving the mechanical reliability of optical fibers.

Hollow core photonic crystal fiber, as a new type of special fiber, can be used in resonant fiber gyroscopes to prepare high-performance miniaturized resonant cavities, with strong environmental anti-interference ability and the advantage of reducing nonlinear optical noise. This paper proposes a single beam splitter reflective spatial micro mirror coupling scheme on a silicon-based optical platform to address the issue of excessive fusion losses in hollow core optical fibers. The scheme achieves a small-sized and low coupling loss hollow core photonic crystal fiber resonant cavity, while providing a compensation interface for the stability of the incoming optical power. Combined with an optical power feedback module, it can effectively suppress optical Kerr noise in the system. The characteristics of miniaturization and temperature insensitivity of hollow core photonic crystal fiber resonant cavity are studied. Finally, the resonant cavity is tested, and the results show that the coupling loss of the resonant cavity is 0.28 dB, and the output precision is 19.4, which is currently the best level among similar schemes. After feedback compensation, the forward and backward light power difference is 17.5 nW, and the system detection accuracy determined by optical Kerr noise reaches 0.07 °/h, meeting the high-precision gyroscope accuracy requirements.

In response to the fiber optic circuit failure of Nanrui Optical CT at Lingzhou Station, the fiber optic status is analyzed by OTDR technology and the failure point is successfully located. Through on-site inspection, it is found that the fault is caused by icing of the penetrating tube, which results in increased attenuation of the fiber optic cable after being squeezed. Then, in order to investigate the failure and consequences caused by icing through the pipe, the low-temperature icing experiments on four kinds of optical fibers are conducted. It is found that the 4-core fiber optic cables（GYPFJS-4B1）provided by YOFC and the 6-core fiber optic cables with center tube（GYMXTW-48B1.3）provided by Fiberhome have insignificant changes in average attenuation in the process of temperature change, and they have a good fiber optic and fiber optic cable structural design. It can satisfy the requirements of pipe laying in a low-temperature environment, and provide a data basis for improving the reliability of the optical CTs in low-temperature environment applications.

Aiming at the problem that traditional electronic sensors have large electromagnetic interference in partial discharge monitoring of gas-insulated metal-closed transmission lines（GIL）, the interferometry of partial discharge signals based on distributed weak fiber Bragg grating（WFBG）is realized in this paper. And a low noise optical fiber interference phase monitoring method based on long short-term memory network（LSTM）transformation for the measured optical phase signals is proposed. Based on LSTM processing, the interference phase wideband noise of WFBG is suppressed, and the correlation of signals at different historical moments is processed, and the change of signal characteristics is compared and analyzed. The results show that the long short term memory network transformation method based on weak reflection grating can be effectively applied to GIL partial discharge monitoring. Compared with traditional algorithms, LSTM algorithm can effectively improve the signal to noise ratio of 7.0 dB, and still has certain advantages in correlation processing compared with traditional GA-BP algorithm, which has certain engineering significance in the field of GIL monitoring.

Single photon detection technology is becoming a development trend in laser detection technology due to its high detection sensitivity and long detection distance, which has attracted a lot of attention from domestic and foreign research teams. Using a kHz high-frequency pulse laser as the laser pulse emission source and a 64 × 64 Geiger mode APD array as the detector, short range target experiments are conducted under daytime environmental conditions. By fitting the histogram of photon echo response before and after noise filtering, the standard deviation of Poisson fitting parameters for pixel［30 28］after noise filtering is 1.16, the standard deviation of normal fitting parameters is 0.22 and 0.16, and the expected values are both 130.11. Pixel［40 35］also exhibits the same characteristics. The results indicate that normal distribution fitting has higher accuracy and can provide reference for simulation analysis of photon echo response.

At present, the high power nanosecond 532 nm laser is generally an all-solid system. But stability of the solid laser is poor, which limits the application range of nanosecond 532 nm laser. In this paper, the 532 nm laser is composed of all fiber 1 064 nm laser and spatial frequency doubling. The pulse width is 2.475 ns, the repetition frequency can be adjustable from 100 kHz to 5 000 kHz, the average power is 100.2 W@800 kHz, and the frequency doubling conversion efficiency is 77.6%. The beam quality of green light is Mx2 =1.197, My2 =1.193. The nanosecond green laser has the advantages of high beam quality, high average power, convenient flexible integration and compact structure, and can be used as an ideal light source in the fields of superhard and brittle materials processing and silicon etching.

In continuous terahertz imaging systems, the low intensity of the terahertz source and susceptibility to external environmental interference result in issues such as low signal-to-noise ratio and blurred boundaries in the images. To address these problems, a method utilizing the Unet deep learning network for image defect recognition is proposed. Theoretically, a training dataset is constructed using terahertz images collected through experiments, and the Unet network is trained with this dataset to learn the feature information of the data. Subsequently, the network predicts and outputs defects in images from the test dataset. An experimental system is built concurrently with the theoretical design for validation, and quantitative analysis is conducted by calculating the information entropy and EOG values of the images before and after recognition. The results indicate that the predicted images exhibit an 8.03% increase in information entropy and a 13.61% increase in EOG values compared to the original images, demonstrating that the network significantly enhances image clarity and visual quality.

To study the dynamic performance of an integrated rectangular mirror used for THz ultra high speed imaging, a random vibration response analysis is conducted on its structure. This paper elaborates on the random vibration response analysis method based on random basic excitation, and designs a finite element model of an integrated rectangular rotating mirror using the finite element simulation analysis software ANSYS. And compared the results of modal module simulation analysis with real measurements, it is found that the difference between simulation calculation and actual data is less than 4%, which verifies the correctness and accuracy of the established model. For the vibration response of an integrated rectangular-like rotating mirror under axial and radial random excitations, finite element random vibration response calculations are performed. By comparing the random vibration experiments under axial excitation with the simulated analysis results, the probability that the rotating mirror is subjected to a stress exceeding 37.029 MPa is only 0.3%, which is far lower than the yield limit strength of the material. The study identifies some issues in the current design and summarized preliminary improvement plans through analysis, and provides important reference for future research and development of rotating mirrors.

Infrared temperature measurement technology is a commonly used technique for equipment fault detection in the power industry, which has significant applications in diagnosing faults for high-voltage substation equipment. To improve the accuracy of temperature measurement, an infrared temperature measurement model based on thermal radiation theory is established, and a comprehensive transmittance correction method is proposed. First, an infrared temperature measurement model is constructed based on the theory of thermal radiation, and this model is simplified according to practical application environments. Then, the influence of SF6 gas transmittance on temperature measurement is taken into consideration, and corresponding transmittance correction method is developed to improve the accuracy of temperature measurement. Finally, practical temperature measurement experiments are conducted to verify the effectiveness of the established model and proposed transmittance correction method. The experimental results show that compared with the situation without transmittance correction, the accuracy of infrared temperature measurement is significantly improved after using the comprehensive transmittance correction method. The maximum reduction rate of measurement error before and after transmittance correction is 78.6%. This method lays a solid foundation for fault detection and monitoring of the power grid and shows broad application prospects for its safe operations.

The roof prism plays a crucial role in optical sighting systems, serving functions such as adjusting light paths, rotating images, directing reflections, and shortening optical paths. With the increasing precision requirements of optical systems, there is a stringent demand for accuracy in the angular errors, surface shape errors, and surface roughness of roof prisms, presenting a significant challenge in the optical manufacturing industry. Consequently, research on high-precision calibration prism processing technology is proposed. Firstly, a process analysis of high-precision roof prisms is provided, and the key difficulties and critical points in prism fabrication are pointed out. Subsequently, the design of high-precision calibration prism processing schemes, the methods of processing technology, and their implementation are elaborated. The detection and control methods for achieving a spatial 90° angle are adressed, resulting in an increase in the first-pass yield of parts from 5% to approximately 60%. Additionally, a dedicated repair fixture is designed, leading to an increase in the yield rate to over 80% after a single repair. It presents an optimization of the processing technology for ridge prisms, resulting in improved machining precision and higher yield rates. This advancement is of significant importance to the optical manufacturing industry, particularly in the production of high-precision optical components.

In view of the limitations of the use of existing inertial frame alignment algorithms without latitude , there is an error accumulation phenomenon caused by the latitude estimation error. An optimized initial alignment method based on damped Gauss-Newton iteration without latitude is proposed in this paper. First of all, a new inertial frame alignment model is constructed, during the constructing process of latitude-related gravity vector, separating the latitude information-related items, to reduce the effect of the latitude estimation error on the accuracy of the model. And then the gravity visual motion principle is adopted to estimate latitude, and the damped Gauss-Newton iteration is adopted to solve non-linear least square question, which can solve constant attitude quaternion. Finally, for the error source in the gravity vector under the inertial solidification coordinate frame, real-time wavelet noise reduction and adaptive Kalman filter（RWD-AKF）algorithm are designed to optimize and reconstruct it, to further improve the latitude estimation accuracy and alignment accuracy. Sway simulation trial proves: compared with existing latitude-free alignment method（TVA）, the proposed alignment method without latitude results in a heading alignment accuracy improvement of more than 30%, close to the conventional OBA alignment accuracy. The proposed alignment method can effectively realize the alignment of the SINS without latitude, to improve the flexibility and universality of SINS.

When only single-point position information is provided, the commonly used combined navigation algorithms based on Kalman filtering still have limitations in error correction for inertial navigation systems. These algorithms struggle to comprehensively reflect the complex dynamic changes of inertial navigation systems and fail to effectively suppress the cumulative errors of such systems. Additionally, due to the insufficient research on the laws of navigation errors after single-point position correction, significant positioning and attitude errors persist in inertial navigation systems even after single-point position correction, severely affecting the accuracy and reliability of the navigation systems. The paper analyzes the internal mechanisms and laws of single-point correction through theoretical derivations, simulation verifications, and other methods. The research shows that the effectiveness of single-point position correction is related to the correction time. Correction performed when the heading error is zero yields the best results, achieving an error readjustment rate of over 90%. Moreover, the phase of the heading oscillation error is reset to zero after single-point position correction at any time. These findings can effectively guide subsequent research and applications of single-point position correction.

In order to improve the operational efficiency of medium and long-range precision strike equipment in complex battlefield environment, and to realize medium/long-wave, common aperture, high resolution and athermalization in photoelectric detection system, a high resolution athermal infrared optical system with composite common aperture of medium/long-wave is designed. The system selects the strapdown general structure design with high maturity and stability. Based on medium/long-wave combined cooling infrared 640×512 pixel detector with pixel size of 24 m, the system uses one imaging with four-piece optical structure, and introduces a binary diffraction plane. The parameters of the optical system are as follows: the system focal length is 19 mm, field size is 44°×35°, the optical distortion is less than 2%, the cold diaphragm efficiency is 100%, and the modulation transfer function curve is straight. The light collecting ability is strong, the structure is simple, and the reliability is high. In the working environment within the temperature range of -40~+70℃, the cooling infrared system has excellent imaging quality and strong environmental adaptability in the medium/long-wave band, and satisfies the usage requirements.

Under the influence of scattering medium, in order to achieve the polarization imaging of long-distance targets, a sub-aperture transceiver integrated optical system for single-pixel polarization imaging is designed. Based on the split-aperture polarization imaging technology, each sub-aperture obtains a different Stokes vector image of the target reflection to achieve simultaneous polarization imaging. The laser collimation system is combined with the inherent intermediate gap of the sub-aperture structure, so as to realize the “integration of transceiver and receiver” of the optical system. The design field of view of the sub-aperture polarization imaging system is ±0.7°, the focal length is 20.45 mm, the working wavelength is 1 550 nm, the divergence angle of the emission system is less than 0.2 mrad, the total length of the system is less than 240 mm, and the maximum aperture of the telescope objective is 100 mm. The design results show that the received energy of each aperture of the system meets the sensitivity requirements of the detector, and the full Stokes vector of the target can be collected at the same time. Compared with the independent transceiver system, the transmitting and receiving system of this system is coaxial and eliminates the inherent declination angle, which increases the accuracy of the overall system in long-distance target detection, and the system structure is more compact.

To solve the problem of sapphire windows being prone to water accumulation and affecting observation and imaging in marine environments, on the basis of a three band anti-reflection film preparation on sapphire substrate, submicron hollow microsphere framework structure is prepared by self-assembly technology in this paper. The chemical immersion is employed for compositing nanoparticles and forming micro-nano composite structure, which overcomes light reflection and scattering at the submicron scale, and achieves an excellent combination of high transmittance and superhydrophobic properties. After preparation, high temperature, low temperature, humid heat, and salt spray tests are conducted according to the requirements of the optical film environment screening test. After the tests, there is no change in the optical properties and hydrophobicity, maintaining a good hydrophobicity angle of 150°. The experimental results show that the prepared superhydrophobic window has good hydrophobicity and environmental durability, which can meet the long-term use needs of sapphire windows in complex environments.